Patient Specific Computational Modeling in Cardiovascular Mechanics

  • Arthur Creane
  • Daniel J. Kelly
  • Caitríona Lally
Part of the Lecture Notes in Computational Vision and Biomechanics book series (LNCVB, volume 5)

Abstract

Diseases of the cardiovascular system are leading causes of morbidity and mortality worldwide. Computational modeling of cardiovascular mechanics has contributed to the understanding of cardiovascular disease etiology and risk evaluation. Patient specific finite element models of disease sites such as atherosclerotic plaques and aneurysms have provided important insights into their biomechanics, including identification of the characteristics of vulnerable locations.

Current clinical risk assessment for atherosclerotic plaque disruption is based on the stenosis produced by the lesion; however it has been found that the magnitude of stenosis does not correlate with the plaque’s vulnerability. Likewise evaluation of the likelihood of aneurysm rupture is based mainly on diameter measurements; however this criterion has also been called into question. Plaque and aneurysm rupture are often fatal events and thus improved clinical indicators for them are required. Patient specific finite element models of these disease sites may provide improved indicators of vulnerability based on biomechanical principles. Proposed indicators in the literature include measures of maximal stress and stress/strength ratios, additionally geometric measures such as plaque curvature or vessel asymmetry have also been developed as potential indicators.

In recent years, model complexity has increased from 2D studies to 3D models with multiple components. Current technical challenges which are being addressed in the literature include the estimation of the stress free reference configuration of arteries from the deformed in vivo configuration present in medical images and the inclusion of residual stresses in the arterial wall. Furthermore anisotropic constitutive models with artery specific preferred material directions are being implemented in these complex geometries using stress or strain based fiber remodeling algorithms and geometric systems. This chapter reviews the current state of the art in the area and details the barriers yet to be overcome if patient specific computational modeling is to be used as a clinical tool. These include trade-offs between automation, model complexity, computation time and reproducibility.

Keywords

Residual Stress Abdominal Aortic Aneurysm Carotid Plaque Diffusion Tensor Magnetic Resonance Imaging Patient Specific Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

This publication has emanated from research conducted with the financial support of Science Foundation Ireland under Research Frontiers Grant 07/RFP/ENMF660 and grant 07/RFP/ENMF660 TIDA Feasibility 10.

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Copyright information

© Springer Science+Business Media Dordrecht 2012

Authors and Affiliations

  • Arthur Creane
    • 1
  • Daniel J. Kelly
    • 2
  • Caitríona Lally
    • 1
    • 2
  1. 1.School of Mechanical and Manufacturing EngineeringDublin City UniversityDublin 9Ireland
  2. 2.Trinity Centre for Bioengineering, School of EngineeringTrinity CollegeDublin 2Ireland

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